Graduate School of Economics
YAMAMOTO Yohei
  • Curriculum Vitae
  • Research Results
  • Educational and Social Activities

日本語

Paper

1.Testing Jointly for Structural Changes in the Error Variance and Coefficients of a Linear Regression Model(jointly worked)
Quantitative Economics Vol.11,pp.1019-1057 2020 Academic journal
ISSN 1759-7323doi
2.Testing for Changes in Forecasting Performance(jointly worked)
forthcoming in Journal of Business and Economic Statistics 2019 Academic journal
ISSN 0735-0015doi
3.The Exchange Rate Effects of Macro News after the Global Financial Crisis(jointly worked)
Journal of International Money and Finance Vol.95,pp.424-443 2019 Academic journal
ISSN 0261-5606doi
4.Pitfalls of Two-Step Testing for Changes in the Error Variance and Coefficients of a Linear Regression Model(jointly worked)
Econometrics Vol.7,No.2,pp.1-22 2019 Academic journal
ISSN 2225-1146doi
5.Bootstrap Inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions
Journal of Applied Econometrics Vol.34,No.2,pp.247-267 2019 Academic journal
ISSN 0883-7252doi
6.A Modified Confidence Set for the Structural Break Date in Linear Regression Models
Econometric Reviews Vol.37,No.9,pp.974-999 2018 Academic journal
ISSN 0747-4938doi
7.Is the Renminbi a Safe Haven?(jointly worked)
Journal of International Money and Finance Vol.79,pp.189-202 2017 Academic journal
ISSN 0261-5606doi
8.Intra-Safe Haven Currency Behavior During the Global Financial Crisis(jointly worked)
Journal of International Money and Finance Vol.66,pp.49-64 2016 Academic journal
ISSN 0261-5606doi
9.On the Usefulness or Lack Thereof of Optimality Criteria for Structural Change Tests(jointly worked)
Econometric Reviews Vol.35,No.5,pp.782-844 2016 Academic journal
ISSN 0747-4938doi
10.Forecasting with Non-spurious Factors in U.S. Macroeconomic Time Series
Journal of Business and Economic Statistics Vol.34,No.1,pp.81-106 2016 Academic journal
ISSN 0735-0015doi
11.Testing for Factor Loading Structural Change Under Common Breaks(jointly worked)
Journal of Econometrics Vol.189,No.1,pp.187-206 2015 Academic journal
ISSN 0304-4076doi
12.Confidence Sets for the Break Date Based on Optimal Tests(jointly worked)
The Econometrics Journal Vol.18,No.3,pp.412-435 2015 Academic journal
ISSN 1368-4221doi
13.Using OLS to Estimate and Test for Structural Changes in Models with Endogenous Regressors(jointly worked)
Journal of Applied Econometrics Vol.30,pp.119-144 2015 Academic journal
ISSN 0883-7252doi
14.On Structural Change and Forecasting Performance Stability of Japanese Phillips Curve Models (in Japanese)
Journal of the Japan Statistical Society Vol.44,No.1,pp.75-95 2014 Academic journal
ISSN 0389-5602doi
15.Large Versus Small Foreign Exchange Interventions(jointly worked)
Journal of Banking and Finance Vol.43,pp.114-123 2014 Academic journal
ISSN 0378-4266doi
16.A Note on Estimating and Testing for Multiple Structural Changes in Models with Endogenous Regressors via 2SLS(jointly worked)
Econometric Theory Vol.30,No.2,pp.491-507 2014 Academic journal
ISSN 0266-4666doi
17.Estimating and Testing Multiple Structural Changes in Linear Models Using Band Spectral Regressions(jointly worked)
Econometrics Journal Vol.16,No.3,pp.400-429 2013 Academic journal
ISSN 1368-4221doi

Other

1.Reserves and Risk: Evidence from China(jointly worked)
Federal Reserve Bank of Dallas, Globalization Institute Working Paper 387 2020 Other
Link
2.The Great Moderation: Updated Evidence with Joint Tests for Multiple Structural Changes in Variance and Persistence(jointly worked)
HIAS Discussion Paper E-90 2019 Bulletin of university, institute, etc.
HERMES-IR
3.Negative Interest Rate Policy and the Influence of Macroeconomic News on Yields(jointly worked)
Bank of Japan IMES Discussion Paper Series 2019-E-2 2019 Other
Link
4.Identifying Factor-Augmented Vector Autoregression Models via Changes in Shock Variances
HIAS(Hitotsubashi Institute for Advanced Study) Discussion Paper E-72 2018 Bulletin of university, institute, etc.
HERMES-IR
5.Testing for Speculative Bubbles in Large-Dimensional Financial Panel Data Sets(jointly worked)
Graduate School of Economics Hitotsubashi University Discussion Paper No.2016-04 2016 Bulletin of university, institute, etc.
HERMES-IR
6.Asymptotic Inference for Common Factor Models in the Presence of Jumps
Graduate School of Economics Hitotsubashi University Discussion Paper No.2015-05 2015 Bulletin of university, institute, etc.
HERMES-IR
7.Time Instability of the US monetary system: Multiple Break Tests and Reduced Rank TVP VAR(jointly worked)
Working Paper, University of Virginia 2012 Bulletin of university, institute, etc.
HERMES-IR

Oral Presentation

NOName of subject/Conference NameYearSite
1.The Great Moderation: Updated Evidence with Joint Tests for Multiple Structural Changes in Variance and Persistence(Seminar (National Chengchi University))
2020.05National Chengchi University, Taiwan (online)
2.Testing for Speculative Bubbles in Large-Dimensional Financial Panel Data Sets (Nanyang Econometrics Workshop)
2020.01Nanyang Technological University, Singapore
3.Testing Jointly for Structural Changes in the Error Variance and Coefficients of a Linear Regression Model(Applied Statistics and Econometrics Workshop and Data Science Workshop )
2019.11Tohoku University, Sendai, Japan
4.The Great Moderation: Updated Evidence with Joint Tests for Multiple Structural Changes in Variance and Persistence(Macro Workshop)
2019.11Waseda University, Tokyo, Japan
5.Testing Jointly for Structural Changes in the Error Variance and Coefficients of a Linear Regression Model(Economics Seminar)
2019.10National Taipei University, New Taipei City, Taiwan
6.Identifying Factor-Augmented Vector Autoregression Models via Changes in Shock Variances(Helsinki Graduate School of Economics Seminar)
2019.09Helsinki GSE, Helsinki, Finland
7.Testing Jointly for Structural Changes in the Error Variance and Coefficients of a Linear Regression Model(NBER-NSF Time Series Conference)
2019.08Chinese University of Hong Kong, Hong Kong
8.Testing for Speculative Bubbles in Large-Dimensional Financial Panel Data Sets(15th International Symposium on Econometric Theory and Applications)
2019.06Osaka University, Osaka Japan
9.Testing for Speculative Bubbles in Large-Dimensional Financial Panel Data Sets(Pi-Day Econometrics Conference at Boston University)
2019.03Boston University, Boston, USA
10.*Identifying Factor-Augmented Vector Autoregression Models via Changes in Shock Variances(12th International Conference on Computational and Financial Econometrics)
2018.12University of Pisa, Pisa, Italy
11.Identifying Factor-Augmented Vector Autoregression Models via Changes in Shock Variances(Midwest Econometric Conference)
2018.10University of Wisconsin, Madison, USA
12.Identifying Factor-Augmented Vector Autoregression Models via Changes in Shock Variances(Econometrics Seminar)
2018.10Boston University, Boston, USA
13.Identifying Factor-Augmented Vector Autoregression Models via Changes in Shock Variances(CIREQ Seminar)
2018.10McGill University, Montreal, Canada
14.Identifying Factor-Augmented Vector Autoregression Models via Changes in Shock Variances(5th Conference of International Association for Applied Econometrics)
2018.06University of Quebec Montreal, Montreal, Canada
15.Testing for Speculative Bubbles in Large-Dimensional Financial Panel Data Sets(Economic Seminar)
2017.08Academia Sinica, Taipei, Taiwan
16.*Bootstrap Inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions(Workshop on Advances in Econometrics 2017)
2017.06Hakodate, Japan
17.Bootstrap Inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions(4th Conference of International Association for Applied Econometrics)
2017.06Sapporo, Japan
18.*Testing for Speculative Bubbles in Large-Dimensional Financial Panel Data Sets(Workshop on Macroeconomic and Financial Time Series Analysis)
2017.06Lancaster University Management School, Lancaster, UK
19.Bootstrap Inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions(10th International Conference on Computational and Financial Econometrics)
2016.12Universidad de Sevilla, Spain
20.Testing for Speculative Bubbles in Large Dimensional Financial Panel Data Sets(Japan-Korea Allied Conference in Econometrics)
2016.11Hitotsubashi University, Japan
21.Asymptotic Inference for Common Factor Models in the Presence of Jumps(12th International Symposium on Econometric Theory and Applications)
2016.10University of Western Ontario, Canada
22.*Bootstrap Inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions(Hitotsubashi Summer Institute Workshop)
2016.08Hitotsubashi University, Japan
23.Is the Renminbi a Safe Haven?(Twelfth Annual Conference of Asia-Pacific Economic Association)
2016.07International Management Institute Kolkata, Kolkata, India
24.*Asymptotic Inference for Common Factor Models in the Presence of Jumps(The 25th South Taiwan Statistics Conference)
2016.06National Sun Yat-sen University, Kaohsiung, Taiwan
25.*Asymptotic Inference for Common Factor Models in the Presence of Jumps(AJRC and HIAS Joint Conference on Recent Issues in Finance and Macroeconomics)
2016.03The Australian National University, Canberra, Australia
26.Asymptotic Inference for Common Factor Models in the Presence of Jumps(Society for Nonlinear Dynamics and Econometrics 24th Annual Symposium)
2016.03University of Alabama, Tuscaloosa, Alabama, USA
27.Asymptotic Inference for Common Factor Models in the Presence of Jumps(12th International Symposium on Econometric Theory and Applications)
2016.02Waikato Management School, Hamilton, New Zealand
28.Asymptotic Inference for Common Factor Models in the Presence of Jumps(9th International Conference on Computational and Financial Econometrics)
2015.12University of London, UK
29.Asymptotic Inference for Common Factor Models in the Presence of Jumps(Econometrics Seminar)
2015.09Keio University, Japan
30.Asymptotic Inference for Common Factor Models in the Presence of Jumps(Japanese Joint Statistical Meeting)
2015.09Okayama University, Japan
31.*Asymptotic Inference for Common Factor Models in the Presence of Jumps(Hitotsubashi Summer Institute)
2015.08Hitotsubashi University, Japan
32.A Modified Confidence Set for the Structural Break Date in Linear Regression Models(The 2nd Conference of International Association for Applied Econometrics)
2015.06University of Macedonia, Greece
33.*Intra-Safe Haven Currency Behavior During the Global Financial Crisis(International Conference on the New Normal in the Post-Crisis Era)
2015.05City University of Hong Kong
34.A Modified Confidence Set for the Structural Break Date in Linear Regression Models(-)
2015.01Osaka University, Japan
35.On Structural Change and Forecast Performance Stability in Japanese Phillips Curve Models(-)
2015.01Research Center for Advanced Science and Technology, The University of Tokyo, Japan
36.*A Modified Confidence Set for the Structural Break Date in Linear Regression Models(Sogan-Hitotsubashi Conference on Econometrics)
2014.12Sogan University, South Korea
37.Testing for Factor Loading Structural Change under Common Breaks(Canadian Econometric Study Group Annual Meeting)
2014.10Simon Fraser University, Canada
38.A Modified Confidence Set for the Structural Break Date in Linear Regression Models(Summer Workshop on Economic Theory)
2014.08Otaru University of Commerce, Japan
39.On Structural Change and Forecast Performance Stability in Japanese Phillips Curve Models(Macroeconomics Workshop)
2014.06The University of Tokyo
40.Testing for Factor Loading Structural Change under Common Breaks(The 10th International Symposium on Econometric Theory and Applications)
2014.05Academia Sinica
41.Testing for Factor Loading Structural Change under Common Breaks(The Applied Statistics Workshop)
2014.05The University of Tokyo
42.Testing for Factor Loading Structural Change under Common Breaks(Society for Nonlinear Dynamics and Econometrics 22nd Annual Symposium)
2014.04Baruch College CUNY, New York
43.*On Structural Change and Forecast Performance Stability in Japanese Phillips Curve(-)
2014.03Hiroshima University of Economics, Japan
44.Testing for Factor Loading Structural Change Under Common Breaks(-)
2014.01Development Bank of Japan
45.Large Versus Small Foreign Exchange Interventions(-)
2014.01National Graduate Institute for Policy Studies, Japan
46.On Power Properties of Factor Loading Structural Change Tests under Common Breaks(-)
2013.10Hiroshima University, Japan
47.On Power Properties of Factor Loading Structural Change Tests under Common Breaks(-)
2013.09Boston University, USA
48.On Power Properties of Factor Loading Structural Change Tests under Common Breaks(Japanese Joint Statistical Meeting)
2013.09Osaka University, Japan
49.Forecasting with Non-spurious Factors in U.S. Macroeconomic Time Series(Econometric Society European Meeting)
2013.08The University of Gothenburg, Sweden
50.Forecasting with Non-spurious Factors in U.S. Macroeconomic Time Series(Econometric Society Asian Meeting)
2013.08National University of Singapore
51.Forecasting with Non-spurious Factors in U.S. Macroeconomic Time Series(The 9th International Symposium on Econometric Theory and Applications)
2013.07Sungkyunkwan University, South Korea
52.Forecasting with Non-spurious Factors in U.S. Macroeconomic Time Series(Econometric Society Australasian Meeting)
2013.07The University of Sydney, Australia
53.Forecasting with Non-spurious Factors in U.S. Macroeconomic Time Series(2013 Spring Meeting (Japanese Economic Association))
2013.06University of Toyama
54.On Power Properties of Factor Loading Structural Change Tests under Common Breaks(-)
2013.05Kyoto University, Japan
55.*Estimating and Testing Multiple Structural Changes in Linear Models by Band Spectral Regressions(Western Economic Association 10th Biennial Pacific Rim Conference)
2013.03Keio University, Japan
56.*Forecasting with Non-spurious Factors in U.S. Macroeconomic Time Series(International Conference "Frontiers in Macroeconometrics")
2013.03Hitotsubashi University, Japan
57.Forecasting with Non-spurious Factors in U.S. Macroeconomic Time Series(-)
2013.01Hitotsubashi University, Japan
58.On the Usefulness or Lack Thereof of Optimality Criteria for Structural Change Tests(2012 Hitotsubashi-Sogan Conference on Econometrics)
2012.11South Korea
59.Time Instability of the US monetary system: Multiple Break Tests and Reduced Rank TVP VAR(The 11th World Meeting of the International Society for Bayesian Analysis)
2012.06Kyoto, Japan
60.*Bootstrap inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions(Spring Meeting (Japan Association for Applied Economics))
2012.06Fukuoka University, Japan
61.Estimating and Testing Multiple Structural Changes in Linear Models by Band Spectral Regressions(Canadian Econometric Study Group Meeting)
2011.10Ryerson University, Toronto, Canada
62.Bootstrap inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions(2011 North American Summer Meeting of Econometric Society)
2011.06Washington University in St. Louis, St. Louis, MO, USA
63.Bootstrap inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions(The 5th CIREQ Time Series Conference)
2011.05University of Montreal, Montreal, Canada
64.Using OLS to Estimate and Test for Structural Changes in Models with Endogenous Regressors(-)
2011.02Hitotsubashi University, Japan
65.Using OLS to Estimate and Test for Structural Changes in Models with Endogenous Regressors(-)
2010.12Nagoya University, Japan
66.Bootstrap inference for Impulse Response Functions in Factor-Augmented Vector Autoregressions(Canadian Econometric Study Group Meeting)
2010.10The University of British Columbia, Vancouver, Canada

Scientific Research Funds Results

NOResearch subjectResearch itemYear
1.
Scientific Research (C)2019-2021
2.
Scientific Research (C)2016-2018
3.
Young Scientists (B)2013-2015
4.
Scientific Research (A)2017-2019
5.
Scientific Research (A)2013-2016
6.
Scientific Research (B)2013-2015
7.
Scientific Research (A)2012-2015
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